What Is Stress? Dose-Response Effects in
Commonly Used in Vitro Stress Assays1[OPEN]
Hannes Claeys 2, Sofie Van Landeghem, Marieke Dubois, Katrien Maleux, and Dirk Inzé*
Department of Plant Systems Biology, VIB, B–9052 Ghent, Belgium; and Department of Plant Biotechnology
and Bioinformatics, Ghent University, B–9052 Ghent, Belgium
ORCID IDs: 0000-0001-9384-4138 (H.C.); 0000-0002-3217-8407 (D.I.).
In vitro stress assays are commonly used to study the responses of plants to abiotic stress and to assess stress tolerance. A
literature review reveals that most studies use very high stress levels and measure criteria such as germination, plant survival, or
the development of visual symptoms such as bleaching. However, we show that these parameters are indicators of very severe
stress, and such studies thus only provide incomplete information about stress sensitivity in Arabidopsis (Arabidopsis thaliana).
Similarly, transcript analysis revealed that typical stress markers are only induced at high stress levels in young seedlings.
Therefore, tools are needed to study the effects of mild stress. We found that the commonly used stress-inducing agents mannitol,
sorbitol, NaCl, and hydrogen peroxide impact shoot growth in a highly specific and dose-dependent way. Therefore, shoot growth is
a sensitive, relevant, and easily measured phenotype to assess stress tolerance over a wide range of stress levels. Finally, our data
suggest that care should be taken when using mannitol as an osmoticum.
To study the effects of abiotic stress on plants, in
vitro setups are often used as a proxy for the complex
field environments in which plants are subjected to
stress. These experimental setups are based on the
addition of compounds to the growth medium.
Drought, for instance, is simulated by adding osmotica, such as mannitol, sorbitol, or polyethylene glycol
(Verslues et al., 2006), which lower the water potential
of the medium. This makes it harder for plants to extract water, simulating what happens in drying soil.
Similarly, NaCl is added to the medium to expose
plants to salt stress, which is a combination of osmotic
stress, as NaCl also lowers the water potential of the
medium, and Na+ toxicity, mainly important at high
NaCl concentrations (Munns and Tester, 2008). To
simulate general oxidative stress, occurring for instance
under high-light conditions, the medium is supplemented with hydrogen peroxide (H2O2) or paraquat/
methyl viologen, which induce the formation of the
1
This work was supported by Ghent University (Bijzonder
Onderzoeksfonds Methusalem grant no. BOF08/01M00408 and Multidisciplinary Research Partnership Biotechnology for a Sustainable
Economy grant no. 01MRB510W), the Interuniversity Attraction Poles
Program grant no. (IUAP P7/29 MARS), initiated by the Belgian State,
Science Policy Office, the European Community 6th Framework Programme (AGRON-OMICS grant no. LSHG–CT–2006–037704), and the
Research Foundation-Flanders (predoctoral fellowship to H.C.).
2
Present address: Cold Spring Harbor Laboratory, Cold Spring
Harbor, NY 11724.
* Address correspondence to [email protected].
The author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is:
Dirk Inzé ([email protected]).
[OPEN]
Articles can be viewed online without a subscription.
www.plantphysiol.org/cgi/doi/10.1104/pp.113.234641
toxic reactive oxygen species O 2 2 in plant tissues
(Slade, 1966). While these artificial setups are inherently imperfect, they offer practical advantages,
such as tight control of stress level and onset, low
variability, and the ability to grow many plants using
limited space (Verslues et al., 2006; Lawlor, 2013).
Consequently, much of our current knowledge on
stress physiology in Arabidopsis (Arabidopsis thaliana)
is based on the use of these types of artificial stress
conditions, and this resulted in the identification of
many genes that enhance stress tolerance (Munns
and Tester, 2008; Gill and Tuteja, 2010; Deikman
et al., 2012).
An aspect that is usually underestimated in studies
of stress physiology is the great variety in stress levels.
Often, stress is seen as a binary condition, comparing
an arbitrary stress treatment with a control. However,
in natural and field conditions, plants often experience
a wide variety of stress levels, requiring a range of
different response mechanisms. For instance, lifethreatening drought is very different from a transient
mild water deficit and thus elicits different responses
(Claeys and Inzé, 2013). Therefore, genes that confer
tolerance to severe stress may not enhance growth
under more mild stress conditions (Skirycz et al.,
2011b). To address this issue, we performed a quantitative survey of the scientific literature on Arabidopsis
stress physiology using in vitro assays, and for each
relevant publication we determined which stress level
and what types of phenotyping were used to assess
stress responses. Based on the results of this survey,
we exposed Arabidopsis seedlings to a wide range of
salt, osmotic, and oxidative stress, tracking germination
and growth over time and measuring the expression of
marker genes. These experiments confirmed that there
is a highly dose-dependent response of plants to stress,
the nature of which depends on the type of stress, and
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Claeys et al.
that shoot growth is a very sensitive indicator of stress.
Furthermore, current marker genes for stress are only
induced at very severe stress levels, and novel mild
stress markers are needed.
RESULTS
Most Studies Use Very High Concentrations of
Stress-Inducing Agents
To assess which concentrations are commonly used
in literature, PubMed abstracts and open-access articles from PubMed Central, available through the
text-mining resource EVEX (Van Landeghem et al.,
2013a, 2013b), were scanned for keywords related to
salt, osmotic, and oxidative stress in Arabidopsis, and
concentrations of NaCl, mannitol, sorbitol, and H2O2
used in stress assays were automatically extracted,
followed by manual curation. Our analysis showed
that most studies use very severe stress conditions,
with median concentrations of 150 mM NaCl, 300 mM
mannitol/sorbitol, and 10 mM H2O2 (Fig. 1A). Often, a
range of concentrations is used, but this range usually
only starts at high concentrations (typically 50 mM for
NaCl and 100 mM for mannitol/sorbitol). Accordingly,
when all ranges are reduced to their average, the
overall medians do not change (data not shown). For
all papers in which stress tolerance was assessed, we
also analyzed the phenotypes that were used to
quantify this trait (Fig. 1B). These phenotypes were
divided into three major categories: germination/
survival tests, assessment of plant health (usually
based on overall plant morphology and the appearance of bleaching), and growth measurements. This
analysis showed that most studies (almost 60%) measure germination or survival after treatment with
stress-inducing agents, while less than one-half look at
growth parameters. When growth is assessed, in most
cases this is on the basis of root length measurements.
Our observations clearly show that most published
studies expose plants to very high levels of stressinducing agents and, accordingly, record phenotypes
that are associated with very severe stress.
Different Parameters Show Varying Sensitivities to
Abiotic Stress
In order to study the effects of low to high doses of
common stress-inducing agents, we germinated Arabidopsis Columbia-0 (Col-0) seeds on a wide range of
concentrations of mannitol, sorbitol, NaCl, and H2O2
and measured the germination rate, the extent of
bleaching, the root length at 12 d after stratification
(DAS), and the rosette area at 22 DAS. While inherently difficult to extrapolate, these ranges of osmotic
and salt stress should be comparable to what plants
experience in nature: we used 5 to 300 m M mannitol
or sorbitol, corresponding to an osmotic potential of
20.08 to 20.8 MPa, respectively, while the usable
soil water potential for plants ranges from 20.03 to
21.5 MPa (O’Geen, 2012). Similarly, concentrations
ranging from 5 to 300 mM NaCl were used, while
mild to severe salt stress in the field ranges from 40
to 160 mM NaCl (Abrol et al., 1988). For all stresses, it
is clear that the four parameters we tested show very
different sensitivities to the stress level (Fig. 2). The
germination rate was not affected by the concentrations of mannitol, sorbitol, and H2O2 we tested (up
to 300 mM mannitol and 2.5 mM H2O2), while it was
strongly inhibited by NaCl concentrations of 200 mM
and more. However, germination was delayed at
concentrations starting from 150 mM mannitol or
sorbitol, 100 mM NaCl, and 1.75 mM H2O2 (data not
shown). Visible stress symptoms, such as bleaching
and anthocyanin accumulation, were more sensitive
to NaCl and H2O2 than germination, occurring from
75 mM NaCl or 1 mM H2O2 upward. Mannitol and
sorbitol did not elicit these responses. Growth was
the most sensitive parameter we tested, and for osmotic and salt stress, shoot growth (rosette area) was
more strongly inhibited than root growth. These results indicate that shoot growth can be used as a
very sensitive indicator of abiotic stress.
Mannitol, Sorbitol, NaCl, and H2O2 Induce Highly
Dose-Dependent Growth Responses
To get a more accurate view of the effect of the
different stresses on shoot growth, we tracked the rosette area over time, allowing the calculation of relative
growth rates (RGRs), which are less sensitive to changes
in germination time than absolute growth rates. While all
compounds induce highly dose-dependent responses, the
relationship between concentration and growth response
differed significantly between different stress-inducing
agents.
Mannitol had a drastic effect on the final rosette
area, which was already apparent from 5 mM mannitol
upward and leveled off toward high concentrations
(Fig. 3A). Above 25 mM, plants exhibited aberrant and
elongated leaf shapes. At very high concentrations,
plants were very small, dark green, and compact, but
they still had positive growth rates. At higher stress
levels, rosettes also became more compact (Fig. 3A,
inset). The strongest effects of mannitol on growth
rates were seen at early time points (Fig. 3B). At the first
time point, 8 DAS, the RGR behaved as a quadratic
function of the mannitol concentration, illustrating the
drastic decrease in growth rates with increasing mannitol concentrations. This relationship was relaxed at
later time points for low mannitol concentrations (up to
50 mM), indicating the acclimation of growth to mannitol. Strikingly, the response of plants to sorbitol, an
osmoticum that is structurally very similar to mannitol,
was very different: low concentrations had little effect
on shoot growth, and concentrations of 75 mM and
higher were needed to significantly reduce the rosette
area at 22 DAS (Fig. 3C). A similar trend was seen in the
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Dose-Dependent Effects of Abiotic Stress
Figure 1. Literature study of in vitro
stress assays. A, Concentrations of NaCl
and mannitol/sorbitol used to impose
salt and osmotic stress on Arabidopsis
in PubMed Central open-access articles
(n = 216). The median is indicated with
the black lines. B, Phenotypes recorded
to assess stress tolerance in PubMed
Central open-access articles (n = 106).
The different types of growth measurements are further broken down in the
diagram on the right.
growth rates at early time points (Fig. 3D). Similar to
mannitol, there again was a strong acclimation effect, as
at 22 DAS the RGR was not affected by concentrations
of up to 150 mM sorbitol (Fig. 3D).
Salt stress induced a response that was similar to
that of sorbitol: low concentrations (up to 25 mM;
equivalent to 50 mM sorbitol in osmotic equivalents)
had little effect on growth (Fig. 3E). However, once
the NaCl concentration exceeded 25 mM, growth was
strongly inhibited and compactness increased sharply.
These dose-dependent effects were confirmed when
analyzing RGR of young seedlings: at low concentrations, RGRs were not affected, while at higher concentrations, the RGR quickly decreased as a quadratic
function of the concentration (Fig. 3F). As for mannitol and sorbitol treatments, this quadratic relationship relaxed when seedlings got older, reflecting
acclimation.
Finally, H2O2 had a very striking effect on plant
health, as it induced bleaching (Fig. 3G). Bleaching
seemed to be a binary trait with a threshold that was at
1 to 1.25 mM H2O2; at this concentration, some plants
were fully bleached while others appeared to be normal. While bleaching strongly affected plant growth,
growth was also inhibited when plants were exposed
to low concentrations of H 2 O 2 that did not induce
bleaching (Fig. 3G, inset at bottom left). Interestingly,
the bleaching-independent growth inhibition increased
in a linear fashion with increasing H2O2 concentration.
By contrast, rosette compactness was only impacted by
high H2O2 concentrations (Fig. 3G, inset at top right).
Bleached plants showed a strong reduction in growth
rates over time, as can be seen when looking at growth
rates of plants grown on concentrations exceeding 1 mM
H2O2 (Fig. 3H). A possible explanation for this lies in the
fact that bleaching is progressive and abolishes efficient
photosynthesis, and the Suc supplied in the medium
can only sustain plant growth for a short period of time.
This is different from osmotic and salt stress, which
showed a relief of growth inhibition over time due to
acclimation.
Gene Expression Shows Similar
Dose-Dependent Responses
As many stress-responsive genes have previously
been characterized and described, we analyzed whether
their expression patterns show similar dose-dependent
responses to those observed in our growth experiments.
We performed these analyses on young seedlings, at the
time when the effects of stress on their growth rate were
most pronounced. For all types of stress, we measured
gene expression levels of oxidative stress markers
(NAC DOMAIN-CONTAINING PROTEIN32 [NAC032] and
ALDO-KETO REDUCTASE 4C9 [AKR4C9]; Vanderauwera
et al., 2005), abscisic acid (ABA) markers (CYTOCHROME
P450 707A3 [CYP707A3] and NINE-CIS-EPOXYCAROTENOID
DIOXYGENASE3 [NCED3]; Goda et al., 2008), dehydration
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Claeys et al.
Figure 2. Sensitivity of germination, overall plant health, root length, and rosette area to abiotic stress. Root length (n = 20–24)
and rosette area (n = 30–36) are expressed relative to nontreated plants. For germination rate and plant health (as scored by the
appearance of visual stress symptoms, such as bleaching and anthocyanin accumulation), data come from three independent
experiments. Error bars indicate SE.
markers (RESPONSIVE TO DESSICATION 29B [RD29B],
DEHYDRATION-RESPONSIVE ELEMENT BINDING
PROTEIN 2A [DREB2A], and LATE EMBRYOGENESIS
ABUNDANT-LIKE5 [LEA5]; Kilian et al., 2007), and
mild osmotic stress markers (ETHYLENE RESPONSIVE
ELEMENT-BINDING FACTOR5 [ERF5], MYB DOMAIN
PROTEIN51 [MYB51], and WRKY DNA-BINDING
PROTEIN33 [WRKY33]; Dubois et al., 2013; Fig. 4).
The oxidative stress markers were the only transcripts that responded to all four stresses, confirming that all stresses share an oxidative stress
component (Gill and Tuteja, 2010), but this only
occurred at high concentrations (100 m M or greater
mannitol/sorbitol, 75 m M or greater NaCl, or 1.25
m M or greater H 2 O 2 ). Very high levels of salt and
osmotic stress also induced ABA markers and dehydration markers, although the expression of the
latter was highly variable, but both were not induced by low stress levels. Finally, the mild osmotic
stress markers were indeed confirmed to be specific for
osmotic stress in young seedlings and already responded to low concentrations of mannitol and sorbitol,
although, as for the growth response, higher concentrations of sorbitol were needed to achieve the
same effect.
This analysis shows that, already with a limited set of
stress markers, different stress levels induce unique
combinations and expression levels of stress-responsive
genes, indicating that the transcriptome response is
strongly dependent on the stress level.
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Dose-Dependent Effects of Abiotic Stress
Figure 3. Effects of stress on rosette
growth. A, C, E, and G, Projected rosette
areas at 22 DAS (final time point), with
representative images of plants for a range
of mannitol, NaCl, and H2O2 concentrations. The top right insets show rosette
compactness. For H2O2 treatment, the inset at the bottom left shows rosette areas
(dots) and their averages (lines) grouped by
the presence (red) or absence (black) of
substantial bleaching. B, D, F, and H, RGRs
as a function of the stress levels at 8 DAS
(red), 15 DAS (blue), and 22 DAS (green).
At NaCl concentrations greater than 150
mM (E and F), germination or seedling establishment was inhibited, so no growth
data could be obtained for these concentrations, as represented by the dashed lines
on the graphs. Error bars indicate SE. The
letters above the error bars denote significance groups (ANOVA; P , 0.05;
n = 30–36).
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Figure 4. Effects of stress on the expression of selected marker genes. Levels of oxidative stress markers (NAC032 and AKR4C9),
ABA markers (CYP707A3 and NCED3), dehydration markers (LEA5, RD29B, and DREB2A), and mild osmotic stress markers
(ERF5, WRKY33, and MYB51) in complete seedlings are represented as log2 (fold change) compared with nonstressed plants.
Significant changes (ANOVA; P , 0.05; n = 3) are indicated with asterisks.
DISCUSSION
Shoot Growth as an Indicator of Stress Sensitivity
Many published studies about stress signaling expose plants to very high stress levels (median concentrations of 150 mM NaCl and 300 mM mannitol/
sorbitol) and score very pronounced phenotypes
such as germination rate, seedling survival, or bleaching. To illustrate this, the rosette area was reduced by
more than 95% when we exposed plants to these high
concentrations of mannitol, sorbitol, and NaCl, and saltstressed plants showed additional symptoms of severe
stress such as bleaching. However, plants often experience stresses that are not immediately life threatening
but that do impact growth and productivity (Claeys
and Inzé, 2013). Here, we confirmed that low stress
levels can already severely limit shoot growth without
leading to other visible stress phenotypes, as shown in
previous reports (Granier et al., 2006; Harb et al., 2010;
Skirycz et al., 2010, 2011a; Baerenfaller et al., 2012).
These findings are quite remarkable, in particular because all growth media contained 1% (w/v) Suc. We
mainly chose to add Suc to the medium to replicate the
experimental conditions that are often used to study
abiotic stress in vitro, where Suc-supplemented medium is typically used because it reduces variation in
growth. However, Suc is known to enhance stress
tolerance and affect ABA signaling (Finkelstein and
Gibson, 2002) and could counteract the negative effects
of oxidative stress on photosynthesis that potentially
limit growth (Ramel et al., 2007). The fact that we still
see strong growth inhibition using low stress levels
with Suc-containing media fits with the current view
that stress-induced growth inhibition is an active process that is not dependent on carbon limitation (Claeys
and Inzé, 2013). Our results thus indicate that shoot
growth can be used as a sensitive indicator of stress
tolerance, while root growth, which is more commonly
measured, is less sensitive to abiotic stress (Hsiao and
Xu, 2000; Verslues et al., 2006). Phenotypes such as
germination rate and root growth are most commonly
recorded, possibly because this type of measurement
is perceived to be less labor intensive than measuring
shoot growth. However, by regularly taking photographs of plates or pots containing plants, shoot
growth can easily be tracked over time at the rosette
level. Moreover, several experimental setups have
been specifically designed to automatically track
rosette growth under control and a range of mild
stress conditions, both in soil and in vitro (Granier
et al., 2006; Skirycz et al., 2011b; Dubois et al., 2013;
Tisné et al., 2013). Additionally, at the end of the
experiment, individual leaf areas and cellular parameters can be measured, providing very detailed
information on the impact of stress on growth. This
allows one to study responses to mild stress, at
which point commonly recorded stress phenotypes
are not yet affected.
Current Stress Marker Genes Are Indicators of Severe
Stress in Young Seedlings
For all four stresses, the expression of a number of
known stress-induced genes was measured in young
seedlings. Salt and osmotic stress led to the induction
of dehydration, oxidative stress, and ABA markers,
but only at very high stress levels that caused visible
stress phenotypes, indicating that there most likely
already was cellular damage. The molecular response
to mild osmotic stress is very different, as was shown
previously (Skirycz et al., 2010, 2011a), and marker
genes taken from these studies, such as ERF5, are indeed good indicators that are already induced by low
concentrations of mannitol and sorbitol. However,
these are specific for osmotic stress and are not induced by salt stress, although this stress also has an
osmotic component.
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Dose-Dependent Effects of Abiotic Stress
While some studies attempted to study molecular
responses at different stress levels, this was usually
done in progressive soil-drying experiments (Cramer
et al., 2007; Harb et al., 2010; Bonhomme et al., 2012),
where the time factor cannot be separated from the
stress severity factor. To our knowledge, no dedicated
controlled studies have been performed on the effects
of stress severity on gene expression. Based on the data
presented here for osmotic stress, we postulate that
there may not be a simple linear response in which the
expression of individual genes correlates with the
stress level but that different stress levels to some extent switch on entirely different transcriptomes. This is
similar to what is seen when different stresses are
combined, resulting in transcriptome changes that are
different from those induced by single stresses (Rizhsky
et al., 2004; Rasmussen et al., 2013). Accordingly, there
is no correlation between enhanced survival under severe stress conditions and improved growth under mild
stress conditions, because different mechanisms are involved (Skirycz et al., 2011b).
only limited overlap (Kreps et al., 2002; Zeller et al.,
2009), and the signaling pathways involved are also
distinct (Chinnusamy et al., 2004). Accordingly, it
was shown that major regulators of the response
to mannitol-induced osmotic stress do not to play
any role in the response to mild salt stress (Dubois
et al., 2013).
The response to H 2 O 2 is more complicated due to
the induction of bleaching, but our analysis shows
that bleaching-independent growth inhibition increases linearly with the H2O2 concentration. Finally,
our gene expression data confirm that severe osmotic
and salt stress induce oxidative stress, and this contributes to stress responses, both by inducing damage
and by playing a role in signaling (Gill and Tuteja,
2010; Mittler et al., 2011). Thus, although all abiotic
stresses are often grouped and share certain underlying components, plants respond to these stresses
very differently.
What Is Stress?
Osmotic, Salt, and Oxidative Stress Elicit Very
Different Responses
While all four stress-inducing compounds affect
growth, there are major differences in the extent and
kinetics of growth inhibition. Plant growth is extremely sensitive to mannitol and growth rates drop
rapidly when plants are exposed to low concentrations, but this effect levels off as mannitol levels increase. However, for sorbitol, the other osmoticum we
tested, this was not the case, and 75 mM sorbitol was
needed to induce significant growth inhibition. Recently, it was reported that Col-0, the Arabidopsis accession we used, contains a pair of specific receptors
for mannitol, triggering growth arrest (Trontin et al.,
2014). This is thought to be a biotic stress response,
because many fungi produce mannitol, and is thus
distinct from generic osmotic stress effects. Mannitol
thus induces a combination of biotic and osmotic
stress, explaining the high sensitivity of growth to this
compound. Low concentrations of NaCl, on the other
hand, have little effect on plant growth, echoing the
sorbitol-induced osmotic stress response, but growth
inhibition increases as NaCl levels rise, up to a point
where germination and seedling establishment are
completely inhibited. Plants thus respond to salt stress
in a comparable way as to osmotic stress, but with the
added effect of Na+ toxicity at high concentrations, as
reported previously (Munns and Tester, 2008).
However, we found pronounced gene expression
differences in response to osmotic and salt stress; for
instance, ERF5 was strongly induced by mannitol and
sorbitol but not by NaCl. These differences are very
interesting, as salt and osmotic stress are often grouped
together because they share an osmotic component
(Munns, 2002). However, the transcriptome responses
to salt and osmotic stress have been found to exhibit
The effects of plant growth and gene expression in
response to stress are highly dose responsive, suggesting the existence of very sensitive machinery
assessing the stress level and fine-tuning molecular
responses. Our findings have important consequences
for studying stress physiology. To assess whether
plants are stressed, researchers often rely on strong
visible stress phenotypes or the induction of established stress markers. This strategy can be especially
misleading when used to assess whether the growth
of mutant or transgenic lines is impacted by changes
in stress signaling pathways, as we show here that
growth can be strongly inhibited without classical
signs of stress.
The study of stress responses in plants has thus far
mainly focused on severe and acute stress. However,
stress is traditionally defined as any adverse environmental parameter that limits plant growth and
productivity (Boyer, 1982), and these effects can be
very subtle. The current understanding of the molecular networks underlying growth and survival
responses to stress is still limited, but this regulation
is most likely highly complex and dependent on
parameters such as stress severity, organ or cell
identity, and developmental stage (Claeys and Inzé,
2013). By tracking sensitive parameters such as
shoot growth over a range of stress levels, rather
than traditional severe stress parameters such as
germination, visible stress symptoms, or root growth,
a more accurate picture may be obtained of the stress
sensitivity of, for instance, an ecotype or a transgenic
line. Since it is becoming increasingly clear that there
is no magic bullet that will improve stress tolerance
in all conditions (Tardieu, 2012; Claeys and Inzé,
2013), tools to study the resilience of growth in response to mild stress are needed to improve stress
tolerance.
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MATERIALS AND METHODS
Plant Growth
Seedlings of Arabidopsis (Arabidopsis thaliana) accession Col-0 were grown
in vitro in one-half-strength Murashige and Skoog medium (Murashige and
Skoog, 1962) supplemented with 1% (w/v) Suc for all experiments and different concentrations of D-mannitol (Sigma-Aldrich), sorbitol (Sigma-Aldrich),
NaCl (VWR), or H2O2 (Merck) depending on the experiment. For most experiments, 12 seeds were equally distributed on a 150-mm-diameter plate,
while for root growth experiments, eight seeds were equally distributed on a
plate that was placed vertically. Plants were grown at 21°C under a 16-h-day
(110 mmol m22 s21) and 8-h-night regime. Three biological replicates were
performed for each experiment.
Measurement of Germination, Growth, and Development
Germination (including successful seedling establishment) and symptoms
of severe stress, such as the presence of bleaching or purple spots, were scored
at 22 DAS. At this time point, photographs were taken of each plate, and
projected rosette areas were measured using ImageJ version 1.46 (National
Institutes of Health; http://rsb.info.nih.gov/ij/). For root growth, photographs were taken at 12 DAS, and the primary root length was measured
using ImageJ. The presented germination rates and proportions of healthy
plants are averages over the three experiments. For rosette and root growth,
ANOVA showed that the experiment effect was not significant. Therefore,
experiments were combined, and the presented data are from 30 to 36 plants
for rosette area and 20 to 24 plants for root length.
Rosette Growth Analysis
Photographs were taken of each plate at 8, 11, 13, 15, 18, 20, and 22 DAS.
Projected rosette areas were measured using ImageJ. Rosette compactness was
calculated by dividing rosette area by the area of the convex hull, which were
both measured using ImageJ. Growth was modeled in SAS 9.3 using linear
mixed models. Due to the lack of significant experiment effects, the experiment factor was excluded from the model. Different types of models were
tested, and for all experiments, a linear model with random intercepts and
slopes in which the mean natural logarithm-transformed rosette area was
expressed as a second-order function of time, using the concentration as a
factor, showed the best fit to the experimental data. RGRs were then calculated
as the first-order derivative of the resulting function. All other statistical
analyses were performed in R (version 2.10.1).
Gene Expression Analysis
At 8 DAS, 12 complete seedlings were harvested from one plate per biological replicate. RNA was extracted with Trizol (Invitrogen), followed by a
clean-up step with the RNeasy Mini Kit (Qiagen) including on-column DNase
I (Qiagen) treatment according to the manufacturer’s instructions. Complementary DNA was synthesized with the iScript cDNA Synthesis Kit (Bio-Rad)
according to the manufacturer’s instructions, starting from 1 mg of RNA.
Primers were designed with QuantPrime (Arvidsson et al., 2008). Quantitative
reverse transcription-PCR was performed on a LightCycler 480 (Roche Diagnostics) on 384-well plates with LightCycler 480 SYBR Green I Master (Roche)
according to the manufacturer’s instructions. Melting curves were analyzed to
check primer specificity. Expression values of AT1G13320, AT2G32170, and
AT2G28390 were used for normalization (Czechowski et al., 2005).
Text Mining
To facilitate our literature analysis of compound concentrations used in
previously published studies, we implemented custom text-mining methods.
These methods were applied on all 22 million PubMed abstracts and 460,000
PubMed Central open-access full-text articles available through the text-mining
resource EVEX (Van Landeghem et al., 2013a, 2013b). Texts were restricted to
studies on Arabidopsis through a keyword search, and articles that mentioned
abiotic stress, salt stress, osmotic stress, or oxidative stress were identified,
performing case-insensitive matching throughout the article text and allowing
for lexical variations such as hyphens. The resulting set of articles was processed with a novel rule-based text-mining algorithm that attempts to find
patterns of the form ,QUANTITY MEASURE COMPOUND. such as
“100 mM NaCl” or ,COMPOUND QUANTITY MEASURE. such as “NaCl,
100 mM,” ignoring punctuation marks such as commas and parentheses. To
identify the four compounds of interest (salt, H2O2, mannitol, and sorbitol), a
list of synonyms was compiled to be used during pattern matching, including
the words “salt,” “NaCl,” and “sodium chloride.” Similarly, a list of candidate
terms describing units of measurement, such as “mM,” “millimolar,” “micromolar,” and “molar,” was applied. In a final step, all data were verified and
corrected manually to ensure a high quality.
ACKNOWLEDGMENTS
We thank the Systems Biology of Yield group for the stimulating scientific
atmosphere, Dr. Leentje Jansen for helpful suggestions to improve the
manuscript, and Dr. Annick Bleys for help in preparing the manuscript.
Received December 26, 2013; accepted April 6, 2014; published April 7, 2014.
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